100+ datasets found
  1. Leading websites worldwide 2024, by monthly visits

    • statista.com
    • ai-chatbox.pro
    • +21more
    Updated Mar 24, 2025
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    Statista (2025). Leading websites worldwide 2024, by monthly visits [Dataset]. https://www.statista.com/statistics/1201880/most-visited-websites-worldwide/
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    Dataset updated
    Mar 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2024
    Area covered
    Worldwide
    Description

    In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

  2. Web traffic referrers to Facebook.com 2024

    • ai-chatbox.pro
    • statista.com
    Updated May 30, 2025
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    Tiago Bianchi (2025). Web traffic referrers to Facebook.com 2024 [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstudy%2F9711%2Ffacebook-statista-dossier%2F%23XgboD02vawLYpGJjSPEePEUG%2FVFd%2Bik%3D
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    Dataset updated
    May 30, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Tiago Bianchi
    Description

    As of March 2024, Google.com accounted for over 7.35 percent of referral traffic to Facebook.com. Facebook's second-largest referral traffic driver was msn.com, which generated 4.83 percent of referral traffic to the social media platform. Overall, referrals accounted for slightly less than two percent of traffic to Facebook.

  3. Leading websites in Canada 2023, by monthly traffic

    • statista.com
    Updated Sep 24, 2024
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    Statista (2024). Leading websites in Canada 2023, by monthly traffic [Dataset]. https://www.statista.com/statistics/1047699/canada-websites-ranking-by-average-monthly-traffic/
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    Dataset updated
    Sep 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 1, 2023 - Nov 30, 2023
    Area covered
    Canada
    Description

    From September to November 2023, search platform Google.com was the top ranking website in Canada, with average monthly traffic of almost four billion visits. YouTube ranked second with almost three billion visits. Social network Facebook.com ranked third, with total monthly traffic of 470 million visits.

  4. i

    Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and...

    • ieee-dataport.org
    Updated Oct 21, 2024
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    Mohamad Amar Irsyad Mohd Aminuddin (2024). Website Fingerprinting Dataset of Browsing Network Traffic for Desktop and Mobile Webpages [Dataset]. https://ieee-dataport.org/documents/website-fingerprinting-dataset-browsing-network-traffic-desktop-and-mobile-webpages
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    Dataset updated
    Oct 21, 2024
    Authors
    Mohamad Amar Irsyad Mohd Aminuddin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a dataset of Tor cell file extracted from browsing simulation using Tor Browser. The simulations cover both desktop and mobile webpages. The data collection process was using WFP-Collector tool (https://github.com/irsyadpage/WFP-Collector). All the neccessary configuration to perform the simulation as detailed in the tool repository.The webpage URL is selected by using the first 100 website based on: https://dataforseo.com/free-seo-stats/top-1000-websites.Each webpage URL is visited 90 times for each deskop and mobile browsing mode.

  5. Z

    Network Traffic Analysis: Data and Code

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jun 12, 2024
    + more versions
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    Homan, Sophia (2024). Network Traffic Analysis: Data and Code [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11479410
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    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Moran, Madeline
    Honig, Joshua
    Soni, Shreena
    Homan, Sophia
    Ferrell, Nathan
    Chan-Tin, Eric
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Code:

    Packet_Features_Generator.py & Features.py

    To run this code:

    pkt_features.py [-h] -i TXTFILE [-x X] [-y Y] [-z Z] [-ml] [-s S] -j

    -h, --help show this help message and exit -i TXTFILE input text file -x X Add first X number of total packets as features. -y Y Add first Y number of negative packets as features. -z Z Add first Z number of positive packets as features. -ml Output to text file all websites in the format of websiteNumber1,feature1,feature2,... -s S Generate samples using size s. -j

    Purpose:

    Turns a text file containing lists of incomeing and outgoing network packet sizes into separate website objects with associative features.

    Uses Features.py to calcualte the features.

    startMachineLearning.sh & machineLearning.py

    To run this code:

    bash startMachineLearning.sh

    This code then runs machineLearning.py in a tmux session with the nessisary file paths and flags

    Options (to be edited within this file):

    --evaluate-only to test 5 fold cross validation accuracy

    --test-scaling-normalization to test 6 different combinations of scalers and normalizers

    Note: once the best combination is determined, it should be added to the data_preprocessing function in machineLearning.py for future use

    --grid-search to test the best grid search hyperparameters - note: the possible hyperparameters must be added to train_model under 'if not evaluateOnly:' - once best hyperparameters are determined, add them to train_model under 'if evaluateOnly:'

    Purpose:

    Using the .ml file generated by Packet_Features_Generator.py & Features.py, this program trains a RandomForest Classifier on the provided data and provides results using cross validation. These results include the best scaling and normailzation options for each data set as well as the best grid search hyperparameters based on the provided ranges.

    Data

    Encrypted network traffic was collected on an isolated computer visiting different Wikipedia and New York Times articles, different Google search queres (collected in the form of their autocomplete results and their results page), and different actions taken on a Virtual Reality head set.

    Data for this experiment was stored and analyzed in the form of a txt file for each experiment which contains:

    First number is a classification number to denote what website, query, or vr action is taking place.

    The remaining numbers in each line denote:

    The size of a packet,

    and the direction it is traveling.

    negative numbers denote incoming packets

    positive numbers denote outgoing packets

    Figure 4 Data

    This data uses specific lines from the Virtual Reality.txt file.

    The action 'LongText Search' refers to a user searching for "Saint Basils Cathedral" with text in the Wander app.

    The action 'ShortText Search' refers to a user searching for "Mexico" with text in the Wander app.

    The .xlsx and .csv file are identical

    Each file includes (from right to left):

    The origional packet data,

    each line of data organized from smallest to largest packet size in order to calculate the mean and standard deviation of each packet capture,

    and the final Cumulative Distrubution Function (CDF) caluclation that generated the Figure 4 Graph.

  6. Leading websites in the U.S. 2024, based on visit share

    • statista.com
    Updated Nov 12, 2024
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    Statista (2024). Leading websites in the U.S. 2024, based on visit share [Dataset]. https://www.statista.com/statistics/265770/most-popular-us-websites-by-market-share-of-visits/
    Explore at:
    Dataset updated
    Nov 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2024
    Area covered
    United States
    Description

    In March 2024, Google.com was the leading website in the United States. The search platform accounted for over 19 percent of desktop web traffic in the United States, ahead of second-ranked YouTube.com with 10.71 percent.

  7. India: leading websites 2024, by total visits

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). India: leading websites 2024, by total visits [Dataset]. https://www.statista.com/statistics/1108779/india-websites-ranking-by-traffic/
    Explore at:
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2024
    Area covered
    India
    Description

    In November 2024, Google.com held the top spot in India's website rankings, averaging over **** billion monthly visits. YouTube ranked second, with traffic of **** billion visits, while social platforms Instagram.com and Facebook.com followed with *** million and *** million monthly visits each. Internet penetration In the past decade, India has witnessed a remarkable transformation in its digital landscape. This substantial expansion has resulted in extensive digital connectivity, with more than **** of India's *** billion citizens now enjoying internet access. India ranked **** on the Digital Quality of Life Index in 2023, which revealed electronic infrastructure as one of the country’s strengths. YouTube in India As of 2025, India had the world’s largest YouTube user base, figuring over *** million users. The video platform caters to the nation’s tech-savvy denizens as an educational resource and a source of entertainment. Moreover, YouTube has evolved into a dynamic space for digital marketing, especially harnessing the consumer base segment aged below 32 years.

  8. Data from: HTTPS traffic classification

    • kaggle.com
    Updated Mar 11, 2024
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    Đinh Ngọc Ân (2024). HTTPS traffic classification [Dataset]. https://www.kaggle.com/datasets/inhngcn/https-traffic-classification/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 11, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Đinh Ngọc Ân
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The people from Czech are publishing a dataset for the HTTPS traffic classification.

    Since the data were captured mainly in the real backbone network, they omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

    During research, they divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

    They have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. They also used several popular websites that primarily focus on the audience in Czech. The identified traffic classes and their representatives are provided below:

    Live Video Stream Twitch, Czech TV, YouTube Live Video Player DailyMotion, Stream.cz, Vimeo, YouTube Music Player AppleMusic, Spotify, SoundCloud File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive Website and Other Traffic Websites from Alexa Top 1M list

  9. Traces captured by visiting the top 1500 website

    • kaggle.com
    zip
    Updated Aug 25, 2021
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    DNS_dataset (2021). Traces captured by visiting the top 1500 website [Dataset]. https://www.kaggle.com/jacksontang16/traces-captured-by-visiting-the-top-1500-website
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    zip(5852806 bytes)Available download formats
    Dataset updated
    Aug 25, 2021
    Authors
    DNS_dataset
    Description

    Dataset

    This dataset was created by DNS_dataset

    Contents

  10. Data from: Analysis of the Quantitative Impact of Social Networks General...

    • figshare.com
    • produccioncientifica.ucm.es
    doc
    Updated Oct 14, 2022
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    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz (2022). Analysis of the Quantitative Impact of Social Networks General Data.doc [Dataset]. http://doi.org/10.6084/m9.figshare.21329421.v1
    Explore at:
    docAvailable download formats
    Dataset updated
    Oct 14, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
    Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

    Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

  11. Distribution of internet traffic Thailand 2024, by device

    • ai-chatbox.pro
    • statista.com
    Updated Jun 3, 2025
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    Statista Research Department (2025). Distribution of internet traffic Thailand 2024, by device [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstudy%2F102068%2Fmobile-internet-and-apps-in-thailand%2F%23XgboD02vawLYpGJjSPEePEUG%2FVFd%2Bik%3D
    Explore at:
    Dataset updated
    Jun 3, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Thailand
    Description

    According to a report published by DataReportal, as of December 2024, mobile phones had the highest share of web traffic at 57.68 percent in Thailand. By comparison, the share of web traffic on laptops and desktop computers was around 40 percent.

  12. d

    LAcity.org Website Traffic - Page Views

    • catalog.data.gov
    • data.lacity.org
    • +1more
    Updated Nov 29, 2021
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    data.lacity.org (2021). LAcity.org Website Traffic - Page Views [Dataset]. https://catalog.data.gov/dataset/lacity-org-website-traffic-page-views
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    Dataset updated
    Nov 29, 2021
    Dataset provided by
    data.lacity.org
    Area covered
    Los Angeles
    Description

    Top 25 Daily Page Views for the main website of Los Angeles

  13. Web traffic to shein.com in 2024, by country

    • davegsmith.com
    • statista.com
    Updated Feb 29, 2024
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    Statista Research Department (2024). Web traffic to shein.com in 2024, by country [Dataset]. http://davegsmith.com/index-672.html
    Explore at:
    Dataset updated
    Feb 29, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Description

    In 2024, the single country with the highest share of online traffic to shein.com was the United States. Brazil followed, ranking second with about 12 percent of shein.com web traffic coming from the country, followed by France with 6.6 percent.

  14. DataForSEO Labs API for keyword research and search analytics, real-time...

    • datarade.ai
    .json
    Updated Jun 4, 2021
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    DataForSEO (2021). DataForSEO Labs API for keyword research and search analytics, real-time data for all Google locations and languages [Dataset]. https://datarade.ai/data-products/dataforseo-labs-api-for-keyword-research-and-search-analytics-dataforseo
    Explore at:
    .jsonAvailable download formats
    Dataset updated
    Jun 4, 2021
    Dataset provided by
    Authors
    DataForSEO
    Area covered
    Armenia, Cocos (Keeling) Islands, Korea (Democratic People's Republic of), Azerbaijan, Tokelau, Kenya, Isle of Man, Morocco, Mauritania, Micronesia (Federated States of)
    Description

    DataForSEO Labs API offers three powerful keyword research algorithms and historical keyword data:

    • Related Keywords from the “searches related to” element of Google SERP. • Keyword Suggestions that match the specified seed keyword with additional words before, after, or within the seed key phrase. • Keyword Ideas that fall into the same category as specified seed keywords. • Historical Search Volume with current cost-per-click, and competition values.

    Based on in-market categories of Google Ads, you can get keyword ideas from the relevant Categories For Domain and discover relevant Keywords For Categories. You can also obtain Top Google Searches with AdWords and Bing Ads metrics, product categories, and Google SERP data.

    You will find well-rounded ways to scout the competitors:

    • Domain Whois Overview with ranking and traffic info from organic and paid search. • Ranked Keywords that any domain or URL has positions for in SERP. • SERP Competitors and the rankings they hold for the keywords you specify. • Competitors Domain with a full overview of its rankings and traffic from organic and paid search. • Domain Intersection keywords for which both specified domains rank within the same SERPs. • Subdomains for the target domain you specify along with the ranking distribution across organic and paid search. • Relevant Pages of the specified domain with rankings and traffic data. • Domain Rank Overview with ranking and traffic data from organic and paid search. • Historical Rank Overview with historical data on rankings and traffic of the specified domain from organic and paid search. • Page Intersection keywords for which the specified pages rank within the same SERP.

    All DataForSEO Labs API endpoints function in the Live mode. This means you will be provided with the results in response right after sending the necessary parameters with a POST request.

    The limit is 2000 API calls per minute, however, you can contact our support team if your project requires higher rates.

    We offer well-rounded API documentation, GUI for API usage control, comprehensive client libraries for different programming languages, free sandbox API testing, ad hoc integration, and deployment support.

    We have a pay-as-you-go pricing model. You simply add funds to your account and use them to get data. The account balance doesn't expire.

  15. g

    MOBILE DATA PRICE

    • global-relocate.com
    Updated Oct 29, 2024
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    Global Relocate (2024). MOBILE DATA PRICE [Dataset]. https://global-relocate.com/rankings/worldwide-data-pricing
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    Dataset updated
    Oct 29, 2024
    Dataset provided by
    Global Relocate
    Description

    The ranking of internet costs in various countries shows significant differences, driven by economic, political, and infrastructure factors.

  16. Web traffic of selected online food delivery operators U.S. 2025, by monthly...

    • statista.com
    • ai-chatbox.pro
    Updated Apr 17, 2025
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    Statista (2025). Web traffic of selected online food delivery operators U.S. 2025, by monthly visits [Dataset]. https://www.statista.com/statistics/1452425/web-traffic-top-food-delivery-companies-united-states/
    Explore at:
    Dataset updated
    Apr 17, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2024 - Feb 2025
    Area covered
    United States
    Description

    In February 2025, Postmates recorded around 2.3 million visits to its website in the United States, the lowest web traffic figure among selected online food delivery operators in the country. Postmates was acquired by UberEats for 2.6 billion U.S. dollars in November 2020.

  17. u

    Analysis of network performance when confirmed traffic is present in Long...

    • researchdata.up.ac.za
    zip
    Updated Feb 16, 2024
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    Jaco Marais; Gerhardus Hancke; Adnan Abu Mahfouz (2024). Analysis of network performance when confirmed traffic is present in Long Range Wide Area Networks (LoRaWANs) [Dataset]. http://doi.org/10.25403/UPresearchdata.22113050.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Feb 16, 2024
    Dataset provided by
    University of Pretoria
    Authors
    Jaco Marais; Gerhardus Hancke; Adnan Abu Mahfouz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Quantitative data of figures and graphing scripts from the thesis titled 'Developing a congestion management scheme to reduce the impact of congestion in mixed traffic LoRaWANs'. The files contain the processed output of simulations conducted with a modified version of the ns-3 plugin lorawan. Processed simulation output was Pandas dataframes stored in text files. Software used: ns-3 (version 3.30), Jupyter notebooks, Python with packages sem, pandas, seaborn, modified version of lorawan module from signetlabdei. Python scripts refer to Std and Ex, std refers to the standard LoRaWAN module and Ex refers to the Extended version of the module with the algorithms presented in the thesis. Text files contain a legend at the top of all of the fields present in the dataframe.

  18. Top jewelry and luxury product websites in the U.S. 2024, by website traffic...

    • ai-chatbox.pro
    • statista.com
    Updated Nov 21, 2024
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    Statista (2024). Top jewelry and luxury product websites in the U.S. 2024, by website traffic [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1497036%2Ftop-us-jewelry-luxury-product-websites%2F%23XgboD02vawLZsmJjSPEePEUG%2FVFd%2Bik%3D
    Explore at:
    Dataset updated
    Nov 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 2024
    Area covered
    United States
    Description

    In August 2024, saksfifthvenue.com was the most visited website in the jewelry and luxury goods industry in the United States. That month, the website attracted over eight million visitors. Jomashop.com ranked second, with around 7.6 million website visits. Therealreal.com followed, with around 7.6 million site visits.

  19. d

    Cloudflare Radar: Top 1,000,000 Domain Names of the Week - Dataset -...

    • demo.dev.datopian.com
    Updated Mar 18, 2025
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    (2025). Cloudflare Radar: Top 1,000,000 Domain Names of the Week - Dataset - Datopian CKAN instance [Dataset]. https://demo.dev.datopian.com/dataset/participle--cloudflare-radar-top-domain-names-of-the-week
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    Dataset updated
    Mar 18, 2025
    Description

    This dataset provides a list of the top one million domains as monitored by Cloudflare Radar for the week of February 24 to March 3, 2025. The data is useful for analyzing internet trends, domain popularity, and web traffic insights.

  20. Share of mobile internet traffic in global regions 2025

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Share of mobile internet traffic in global regions 2025 [Dataset]. https://www.statista.com/statistics/306528/share-of-mobile-internet-traffic-in-global-regions/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    Worldwide
    Description

    In January 2025 mobile devices excluding tablets accounted for over ** percent of web page views worldwide. Meanwhile, over ** percent of webpage views in Africa were generated via mobile. In contrast, just over half of web traffic in North America still took place via desktop connections with mobile only accounting for **** percent of total web traffic. While regional infrastructure remains an important factor in broadband vs. mobile coverage, most of the world has had their eyes on the recent 5G rollout across the globe, spearheaded by tech-leaders China and the United States. The number of mobile 5G subscriptions worldwide is forecast to reach more than ***** billion by 2028. Social media: room for growth in Africa and southern Asia Overall, more than ** percent of the world’s mobile internet subscribers are also active on social media. A fast-growing market, with newcomers such as TikTok taking the world by storm, marketers have been cashing in on social media’s reach. Overall, social media penetration is highest in Europe and America while in Africa and southern Asia, there is still room for growth. As of 2021, Facebook and Google-owned YouTube are the most popular social media platforms worldwide. Facebook and Instagram are most effective With nearly ***** billion users, it is no wonder that Facebook remains the social media avenue of choice for the majority of marketers across the world. Instagram, meanwhile, was the second most popular outlet. Both platforms are low-cost and support short-form content, known for its universal consumer appeal and answering to the most important benefits of using these kind of platforms for business and advertising purposes.

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Statista (2025). Leading websites worldwide 2024, by monthly visits [Dataset]. https://www.statista.com/statistics/1201880/most-visited-websites-worldwide/
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Leading websites worldwide 2024, by monthly visits

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99 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 24, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Nov 2024
Area covered
Worldwide
Description

In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

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